Table parsing is a critical bottleneck in RAG pipelines for document-heavy domains like finance and logistics. This analysis compares three popular tools: xParse (layout-aware), PaddleOCR (OCR-based), and MinerU (hybrid). Key findings include trade-offs in accuracy for complex tables, processing speed, and ease of agent integration. Developers should consider their specific table structures and latency requirements when choosing a tool. The post also demonstrates how to wrap these parsers as agents for automated document processing workflows.
A practical comparison of xParse, PaddleOCR, and MinerU for table parsing in RAG pipelines, with agent integration insights.